The Patient/Biostatistics Core provides an overall structure for maintaining and connecting all the available patient data related to mutations in the CFTR gene, generates regular summaries for the design and analysis of experiments and observational studies. Core activities will include: integration of new clinical and scientific data into the Toronto CF Database; support for the database on male infertility patients, who comprise the largest identified group of an expanded spectrum of patients affected by mutations in the CFTR gene; creation of data files and analytic strategies to study other atypical phenotypic groups related to CFTR, such as young patients with pancreatitis and adults with chronic lung disease; provision of clinical profiles for individual patients and patient groups to enhance the planning or interpretation of scientific experiments; statistical analysis of core and project data; and timely statistical consulting for the design and interpretation of experiments. A particular focus in the next period will be the acquisition and support of new and developing software for linkage and association analysis of complex genetic traits. SAS software is used for most data management and statistical analysis, including longitudinal regression and survival regression. Other computer programs used for specific purposes include SPLUS (for graphics and sophisticated statistical estimation); Mapmaker/Sibs, SAGE, and GAP (for genetic linkage and association analysis); DBMS/COPY and ConversionsPlus for converting and transferring files between different systems. Increasingly, different types of laboratory data will be retrieved directly from other computer systems within the hospitals, necessitating increased levels of quality control and validity checking to ensure appropriate record linkage and to preserve the confidentiality of identified patient data. Core support will ensure that scientists have access to the most appropriate patient information and material to design experiments, and that research hypotheses and results are related as immediately and precisely as possible to patient data, to define the links between mutations, protein dysfunction, and disease expression. This core encourages collaboration of basic and clinical investigators, and therefore hastens the application of new knowledge to patient management and treatment evaluation.